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Mining Features from the Object-Oriented Source Code of a Collection of Software Variants Using Formal Concept Analysis and Latent Semantic Indexing

机译:使用正式概念分析和潜在语义索引的软件变体集合的面向对象的源代码的挖掘功能

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Companies often develop a set of software variants that share some features and differ in other ones to meet specific requirements. To exploit existing software variants and build a software product line (SPL), a feature model of this SPL must be built as a first step. To do so, it is necessary to mine optional and mandatory features from the source code of the software variants. Thus, we propose, in this paper, a new approach to mine features from the object-oriented source code of a set of software variants based on Formal Concept Analysis and Latent Semantic Indexing. To validate our approach, we applied it on ArgoUML and Mobile Media case studies. The results of this evaluation validate the relevance and the performance of our proposal as most of the features were correctly identified.
机译:公司经常开发一组软件变体,这些软件变体共享一些功能,并在其他方面的不同,以满足特定要求。要利用现有软件变体并构建软件产品线(SPL),必须将该SPL的特征模型作为第一步构建。为此,必须从软件变体的源代码中挖掘可选和强制性功能。因此,我们提出了一种基于正式概念分析和潜在语义索引的一组软件变体的面向对象源代码的新方法。为了验证我们的方法,我们将其应用于Argougl和移动媒体案例研究。此评估结果验证了我们提案的相关性和表现,因为大多数特征被正确识别。

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